Sales Representative

Overview

You sell data and AI consulting engagements to enterprise clients—think Fortune 500 companies that need help modernizing legacy data infrastructure, implementing AI solutions, or fixing data governance problems. You're positioning Paradigm (a 127-person boutique consulting firm) against both smaller niche players and Big 4 firms like Deloitte or Accenture. Most of your conversations are with VPs of Data/Analytics, CTOs, or CDOs who are frustrated with their current tech stack or under board pressure to "do something with AI."

Role Snapshot

Company Context

Stage: Established private company (30+ years in business)

Size: 127 employees

Growth: Stable consulting firm, not a hypergrowth startup. Likely adding capacity based on client demand rather than aggressive expansion.

Market Position: Boutique specialist competing against both Big 4 and smaller niche firms. Not the cheapest option, not the biggest name.

GTM Reality

Pipeline Sources:

• 30% Existing client expansion/renewals - past projects lead to new work
• 40% Outbound prospecting - targeted outreach to VP/C-level at F500 companies
• 30% Referrals and network - 30 years means they have relationships, but you still need to activate them

SDR/AE Structure: Likely self-sourcing or minimal SDR support. You're expected to generate your own pipeline.

SE Support: You'll pull in practice leads or architects for technical deep-dives, but early conversations are all you.

Competitive Landscape

Main Competitors:

• Big 4 consulting (Deloitte, Accenture, PwC) on enterprise deals
• Boutique data/AI specialists (Slalom, Chartis, smaller regional firms)
• Internal IT teams trying to build vs. buy

How They Differentiate: 30 years of experience, boutique attention vs. Big 4 turnover, deep technical expertise vs. pure strategy shops

Common Objections:

• "We're already working with [Big 4 firm]"
• "Our internal team can handle this"
• "We need to see case studies in our specific industry"
• "Your rates are higher than offshore alternatives"

Win Themes:

• Track record with similar-sized enterprises
• Won't staff the project with junior consultants
• Outcome-focused vs. time-and-materials billing (maybe)
• Industry-specific experience (financial services, healthcare, manufacturing)

What You'll Actually Do

Time Breakdown

Prospecting (30%) | Active Deals (40%) | Scoping/Proposals (20%) | Internal (10%)

Key Activities

• Cold outreach to enterprise contacts: You're researching companies with digital transformation initiatives, finding the right VP or C-level contact, and crafting personalized outreach. Most don't respond. You're aiming for 2-3 new qualified conversations per week.

• Discovery calls and needs analysis: When you get a meeting, you're diagnosing their data/AI challenges—legacy system pain, failed internal projects, compliance issues. You're qualifying budget, timeline, and whether they're shopping or actually ready to buy. Many are just exploring.

• Bringing in technical resources for scoping: For serious opportunities, you coordinate architects or practice leads to do technical assessments. You're scheduling these calls, managing stakeholder calendars across their org (IT, business units, procurement), and trying to build consensus.

• Proposal development and negotiation: You work with delivery teams to scope Statement of Work documents, price out projects (resources, timeline, deliverables), and negotiate terms. Lots of redlining, budget constraints, and "can you sharpen your pencil" conversations. Legal review can add weeks.

The Honest Reality

What's Hard

• Long sales cycles with multiple stakeholders: You'll have deals that feel close for months. IT loves you, but Finance or the CIO hasn't signed off. Projects get delayed due to budget freezes, reorgs, or shifting priorities. Your forecast is always uncertain.

• Competing against incumbents and internal teams: Many prospects already have a Big 4 relationship or think their internal team can handle it. You're selling change and external expertise, which means overcoming "not invented here" bias and relationship inertia.

• Heavy customization and scoping work: Every deal is different. You can't just send a standard proposal. You're spending days on custom scoping documents that often don't close. No product to demo—you're selling your team's expertise and a vision of what could be.

What Success Looks Like

• Closing 3-5 six-figure engagements per year ($1.5-2M in bookings)
• Building a pipeline that's 3-4x your quota (because lots will slip or stall)
• Getting past initial meetings to technical scoping discussions (shows real intent)
• Winning competitive situations against bigger firms or lower-cost alternatives

Who You're Selling To

Primary Buyers:

• VP/SVP of Data & Analytics or Chief Data Officers
• CTOs or VPs of IT at mid-market to enterprise companies
• Occasionally business unit leaders (CFO, COO) sponsoring data initiatives

What They Care About:

• Reducing risk on complex projects: They've seen internal projects fail or vendors over-promise. They want confidence you can deliver.
• Specific industry experience: Healthcare companies want healthcare case studies, banks want financial services expertise. Generalist consulting is a harder sell.
• Speed to value vs. cost: They're balancing "we need this done right" with budget constraints and pressure to show ROI quickly.
• Team quality and stability: Who's actually doing the work? They don't want a bait-and-switch with junior consultants after you win the deal.

Requirements

• 3-5+ years selling complex B2B services (consulting, professional services, or enterprise software)
• Experience with consultative, multi-stakeholder sales—comfortable navigating matrixed organizations
• Understanding of data/analytics or digital transformation concepts (you don't need to be technical, but you need to speak the language)
• Track record selling six-figure deals with 3-6+ month cycles
• Comfort with ambiguity and self-direction—this isn't a role with heavy sales ops support or clear playbooks
• Network or relationships in target verticals (financial services, healthcare, manufacturing) is a major plus